Pharmaceutical drug discovery, a multi-billion dollar industry, involves the identification and validation of therapeutic targets, as well as the identification and optimization of lead compounds. The explosion in numbers of potential new targets and chemical entities resulting from genomics and combinatorial chemistry approaches over the past few years has placed enormous pressure on screening programs. The rewards for identification of a useful drug are enormous, but the percentages of hits from any screening program are generally very low. Desirable compound screening methods solve this problem by both allowing for a high throughput so that many individual compounds can be tested; and by providing biologically relevant information so that there is a good correlation between the information generated by the screening assay and the pharmaceutical effectiveness of the compound.
Some of the more important features for pharmaceutical effectiveness are specificity for the targeted cell or disease, a lack of toxicity at relevant dosages, and specific activity of the compound against its molecular target. Therefore, one would like to have a method for screening compounds or libraries of compounds that allows simultaneous evaluation for the effect of a compound on different cellular pathways, where the assay predicts aspects of clinical relevance and potentially of future in vivo performance.
While collecting information about multiple aspects of pharmacologic activity is useful because it provides a more complete analysis of the compound, it also makes the data analysis more difficult, because multiple parameters must be considered. Developments in computing technologies can provide solutions, but must be tied into the matrix of biological information.
In addition, cellular physiology involves multiple pathways, where pathways split and join, redundancies in performing specific actions and responding to a change in one pathway by modifying the activity of a different pathway. In order to understand how a candidate drug is acting and whether it will have the desired effect, it is necessary to know, not only the target protein with which the drug reacts, but whether the inhibition of the protein activity will result in the desired response. The development of screening assays that can provide better, faster and more efficient prediction of mechanisms of action, cellular effects and clinical drug performance is of great interest in a number of fields, and is addressed in the present invention. It is an object of the invention to provide a method for screening for inhibitors or modulators of cellular processes, which provide multiparameter information about the action of the agents tested on multiple cellular pathways.
Relevant Literature
In many assays, cell-free components such as enzymes and their substrates are used for compound screening. For example, U.S. Pat. No. 4,568,649 describes ligand detection systems which employ scintillation counting. In these methods, the therapeutic utility of compounds identified in such assays is presumed from a large body of other evidence previously identifying that a particular enzyme or target may be important to a disease process.
Cell based assays include a variety of methods to measure metabolic activities of cells including: uptake of tagged molecules or metabolic precursors, receptor binding methods, incorporation of tritiated thymidine as a measure of cellular proliferation, uptake of protein or lipid biosynthesis precursors, the binding of radiolabeled or otherwise labeled ligands; assays to measure calcium flux, and a variety of techniques to measure the expression of specific genes or their gene products.
Compounds have also been screened for their ability to inhibit the expression of specific genes in gene reporter assays. For example, Ashby et al. U.S. Pat. No. 5,569,588; Rine and Ashby U.S. Pat. No. 5,777,888 describe a genome reporter matrix approach for comparing the effect of drugs on a panel of reporter genes to reveal effects of a compound on the transcription of a spectrum of genes in the genome.
Methods utilizing genetic sequence microarrays allow the detection of changes in expression patterns in response to stimulus. A few examples include U.S. Pat. No. 6,013,437; Luria et al., “Method for identifying translationally regulated genes”; U.S. Pat. No. 6,004,755, Wang, “Quantitative microarray hybridization assays”; and U.S. Pat. No. 5,994,076, Chenchik et al., “Methods of assaying differential expression”. U.S. Pat. No. 6,146,830, Friend et al. “Method for determining the presence of a number of primary targets of a drug”.
Proteomics techniques have potential for application to pharmaceutical drug screening. These methods require technically complex analysis and comparison of high resolution two-dimensional gels or other separation methods, often followed by mass spectrometry (for reviews see Hatzimanikatis et al. (1999) Biotechnol Prog 15(3):312-8; Blackstock et al. (1999) Trends Biotechnol 17(3):121-7. A discussion of the uses of proteomics in drug discovery may be found in Mullner et al. (1998) Arzneimittelforschung 48(1):93-5.
Various methods have been used to determine the function of a genetic sequence. The initial effort is often performed from sequence information alone. Such techniques can reasonably determine if a new gene encodes a soluble or membrane-bound protein, a member of a known gene family such as the immunoglobulin gene family or the tetraspan gene family, or contains domains associated with particular functions (e.g. calcium binding, SH2 domains etc.). Multiple alignments against a database of known sequences are frequently calculated using an heuristic approach, as described in Altschul et al. (1994) Nat. Genet. 6:119.
Alternatively, “reverse genetics” is used to identify gene function. Techniques include the use of genetically modified cells and animals. A targeted gene may be “knocked out” by site specific recombination, introduction of anti-sense constructs or constructs encoding dominant negative mutations, and the like (see, for some examples, U.S. Pat. No. 5,631,153, Capecchi et al. for methods of creating transgenic animals; Lagna et al. (1998) Curr Top Dev Biol 36:75-98 for an overview of the use of dominant negative constructs; and Nellen et al. (1993) Trends Biochem Sci 18(11):419-23 for a review of anti-sense constructs).
Cells and animals may also be modified by the introduction of genetic function, through the introduction of functional coding sequences corresponding to the genetic sequence of interest. General techniques for the creation of transgenic animals may be found in Mouse Genetics and Transgenics: A Practical Approach (Practical Approach Series) by Ian J. Jackson (Editor), Catherine M. Abbott (Editor). While they have proven useful in many ways, however, transgenic animals frequently suffer from problems of time and expense, as well as compensatory mechanisms, redundancies, pleiotropic genetic effects, and the lethality of certain mutations.
Another approach for discovering the function of genes utilizes gene chips or microarrays. DNA sequences representing all the genes in an organism can be placed on miniature solid supports and used as hybridization substrates to quantitate the expression of all the genes represented in a complex mRNA sample, and assess the effect of a perturbation on gene expression. Methods utilizing genetic sequence microarrays can be applied to pharmaceutical target validation. In these methods, genetic modifications are evaluated for their effects on the expression of particular genes. A few examples include U.S. Pat. No. 6,013,437; Luria et al., “Method for identifying translationally regulated genes”; U.S. Pat. No. 6,004,755, Wang, “Quantitative microarray hybridization assays”; and U.S. Pat. No. 5,994,076, Chenchik et al., “Methods of assaying differential expression”.
Gene reporter assays can also be used to characterize the effect of genetic modifications by their ability to inhibit the expression of specific genes in gene reporter assays. For example, Ashby et al. U.S. Pat. No. 5,569,588; Rine and Ashby U.S. Pat. No. 5,777,888 describe a genome reporter matrix approach for comparing the effect of drugs on a panel of reporter genes to reveal effects of a compound on the transcription of a spectrum of genes in the genome.